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VTune Profiler (formerly VTune Amplifier) is a performance analysis tool for x86-based machines running Linux or Microsoft Windows operating systems. Many features work on both Intel and AMD hardware, but the advanced hardware-based sampling features require an Intel-manufactured CPU.
Features & Overview
Explore the main themes, entities and connections around VTune. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
intel profiler oneapi tool linux features windows operating free performance analysis base toolkit developer website tools amd formerly amplifier x86-based
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| VTune | Developer | Intel Developer Products | 1.00 | infobox |
| VTune | License | Free and Commercial Support | 1.00 | infobox |
| VTune | Operating system | Windows and Linux (UI-only on macOS) | 1.00 | infobox |
| VTune | Stable release | 2024.2 / June 18, 2024; 2 years ago (2024-06-18) | 1.00 | infobox |
| VTune | Type | Profiler | 1.00 | infobox |
| VTune | Website | software.intel.com/content/www/us/en/develop/tools/oneapi/components/vtune-profiler.html | 1.00 | infobox |
| VTune | related to External links | Official | 0.60 | section |
| VTune | related to External links | ProfilerIntel | 0.60 | section |
| VTune | related to External links | Base Toolkit | 0.60 | section |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.